This paper illustrates a new methodology for finding preferred action choice(s) under uncertainty for well-defined classes of decision-makers The methodology does not replace the expected utility maximizing rule, which has been used to identify preferred action choices; rather it extends the rule's accuracy as a positivistic tool and its reliability as a normative guide. The methodology used in this paper does, however, alter the kinds of information needed about decision- makers. Hence, it is related to a practical question facing the Western Regional Research Committee (W-149). This committee is considering estimating utility functions for a large number of decision-makers differentiated by geographic area, commodity produced, farm size, wealth, and other variables and they want to know the value of such a project. Because there was no consensus among the committee, a subcommittee was appointed to explore the question in more detail. This paper can be considered part of that exploration. The remainder of this paper has four parts. In the first, we compare our current interest in utility functions with an earlier interest in production functions and note some similarities. The second part describes how stochastic dominance with respect to a function can be used to identify preferred action choices under uncertainty. The third part illustrates the criterion with a numerical example. And the fourth part concludes with our recommendation for future work on specifying micro risk models.
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Paper provided by Michigan State University, Department of Agricultural, Food, and Resource Economics in its series Agricultural Economic Reports with number
10260.
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